Paciorek Christopher J, Goring Simon J, Thurman Andrew L, Cogbill Charles V, Williams John W, Mladenoff David J, Peters Jody A, Zhu Jun, McLachlan Jason S
Department of Statistics, University of California, Berkeley, California, United States of America.
Department of Geography, University of Wisconsin, Madison, Wisconsin, United States of America.
PLoS One. 2016 Feb 26;11(2):e0150087. doi: 10.1371/journal.pone.0150087. eCollection 2016.
We present a gridded 8 km-resolution data product of the estimated composition of tree taxa at the time of Euro-American settlement of the northeastern United States and the statistical methodology used to produce the product from trees recorded by land surveyors. Composition is defined as the proportion of stems larger than approximately 20 cm diameter at breast height for 22 tree taxa, generally at the genus level. The data come from settlement-era public survey records that are transcribed and then aggregated spatially, giving count data. The domain is divided into two regions, eastern (Maine to Ohio) and midwestern (Indiana to Minnesota). Public Land Survey point data in the midwestern region (ca. 0.8-km resolution) are aggregated to a regular 8 km grid, while data in the eastern region, from Town Proprietor Surveys, are aggregated at the township level in irregularly-shaped local administrative units. The product is based on a Bayesian statistical model fit to the count data that estimates composition on the 8 km grid across the entire domain. The statistical model is designed to handle data from both the regular grid and the irregularly-shaped townships and allows us to estimate composition at locations with no data and to smooth over noise caused by limited counts in locations with data. Critically, the model also allows us to quantify uncertainty in our composition estimates, making the product suitable for applications employing data assimilation. We expect this data product to be useful for understanding the state of vegetation in the northeastern United States prior to large-scale Euro-American settlement. In addition to specific regional questions, the data product can also serve as a baseline against which to investigate how forests and ecosystems change after intensive settlement. The data product is being made available at the NIS data portal as version 1.0.
我们展示了一份网格化的、分辨率为8公里的数据产品,该产品是关于美国东北部欧美移民时期树木分类群的估计组成情况,以及用于从土地测量员记录的树木中生成该产品的统计方法。组成情况被定义为22种树木分类群(通常为属级)中胸径大于约20厘米的树干所占比例。这些数据来自移民时期的公共调查记录,这些记录经过转录后再进行空间汇总,得出计数数据。研究区域分为两个地区,东部(缅因州至俄亥俄州)和中西部(印第安纳州至明尼苏达州)。中西部地区的公共土地测量点数据(约0.8公里分辨率)被汇总到一个规则的8公里网格中,而东部地区来自城镇所有者调查的数据则在形状不规则的当地行政单位的乡镇层面进行汇总。该产品基于一个贝叶斯统计模型,该模型适用于计数数据,可估计整个研究区域8公里网格上的组成情况。该统计模型旨在处理来自规则网格和形状不规则乡镇的数据,并使我们能够估计无数据位置的组成情况,并平滑有数据位置因计数有限而产生的噪声。至关重要的是,该模型还使我们能够量化组成估计中的不确定性,使该产品适用于采用数据同化的应用。我们预计该数据产品将有助于了解美国东北部在大规模欧美移民之前的植被状况。除了特定的区域问题外,该数据产品还可以作为一个基线,用以研究密集移民后森林和生态系统如何变化。该数据产品将作为1.0版本在NIS数据门户网站上提供。